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Update docs and fix tabnet

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Jactus
2020-11-26 00:55:26 +08:00
parent 5be847909f
commit 87cee85cea
27 changed files with 624 additions and 495 deletions
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examples/benchmarks/HATS/README.md
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##Requirement
## Requirement
* pandas==1.1.2
* numpy==1.17.4
* scikit_learn==0.23.2
* torch==1.7.0
##HATS
## HATS
* HATS is a a hierarchical attention network for stock prediction which uses relational data for stock market prediction. HATS selectively aggregates information
on different relation types and adds the information to the representations of each company. HATS is used as a relational modeling module with initialized node representations.Furthermore, HATS

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examples/benchmarks/TFT/README.md
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**GitHub**: https://github.com/google-research/google-research/tree/master/tft
## Run the Workflow
Users can follow the ``workflow_by_code_tft.py`` to run the benchmark.
Users can follow the ``workflow_by_code_tft.py`` to run the benchmark. Please be **aware** that this script can only support Python 3.5 - 3.8.
### Notes
1. The model must run in GPU, or an error will be raised.

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examples/benchmarks/TabNet/workflow_config_tabnet.yaml
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@@ -44,7 +44,7 @@ task:
module_path: qlib.data.dataset
kwargs:
handler:
class: Alpha158
class: ALPHA360_Denoise
module_path: qlib.contrib.data.handler
kwargs: *data_handler_config
segments: